Triple
T1293598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Philippine Sea |
E27601
|
entity |
| Predicate | aircraftLosses |
P28346
|
FINISHED |
| Object | hundreds of Japanese carrier aircraft destroyed |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: hundreds of Japanese carrier aircraft destroyed | Statement: [Battle of the Philippine Sea, aircraftLosses, hundreds of Japanese carrier aircraft destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftLosses Context triple: [Battle of the Philippine Sea, aircraftLosses, hundreds of Japanese carrier aircraft destroyed]
-
A.
aircraftDestroyedUS
Indicates that a U.S. aircraft has been destroyed.
-
B.
aircraftLostByAllies
Indicates that the specified aircraft was lost by Allied forces (e.g., destroyed, missing, or otherwise no longer operational under their control).
-
C.
estimatedAerialVictories
Indicates an approximate count of aerial combat victories attributed to an entity, rather than an exact, confirmed total.
-
D.
survivingAircraftCount
Indicates the number of aircraft that remain operational or intact after a specified event, condition, or time period.
-
E.
aircraftLostByUnitedStates
Indicates that an aircraft was lost (e.g., destroyed, missing, or otherwise no longer operational) and that this loss is attributed to the United States.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c3b9ebdc819098de4d3288201bc1 |
completed | March 1, 2026, 10:54 p.m. |
Created at: March 1, 2026, 7:51 p.m.